Shelf three · Language models & generative AI
Large Language Models
Kitchen table
It has read more than any person ever could – most of the internet, whole libraries – and got astonishingly good at one game: guess the next word. 'The cat sat on the...' You know it is 'mat'. Play that game billions of times with harder and harder sentences and something surprising happens: to guess well, you end up having to know things. But remember it is still guessing. It sounds just as confident when it is wrong, like a friend who never, ever says 'I don't know'.
Whiteboard
Transformers and attention, pretrained on next-token prediction at a scale that turns a party trick into reasoning-shaped behaviour, then aligned with human feedback so the raw predictor becomes an assistant. The capabilities are real and so are the edges: confident interpolation where training data was thin, no native sense of its own uncertainty, and knowledge frozen at the training cut-off. Treat outputs as drafts from a brilliant, occasionally hallucinating colleague – verification is part of the architecture, not an afterthought.
Boardroom
Extraordinary at language work – drafting, summarising, translating, triaging – and unreliable as a source of fact, a combination that decides where it belongs in your business: anywhere a fluent draft saves an expert an hour, nowhere a fabricated detail costs you a customer or a lawsuit unreviewed. The capability is rented from a handful of providers, so concentration risk and pricing power belong on the risk register next to the productivity upside. It is a brilliant drafting colleague, not a database.
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